Businesses seeking to optimize yield from resources constantly balance competing factors in an attempt to increase the efficiency of production. The present disclosure focuses on the environment of a manufacturing plant producing substantially two-dimensional elements for a greater product, for example, individual fabric pieces for a garment, wood and fabric panels for an item of furniture, or metal parts for automobile parts or components of an aeronautical vehicle body made of composite material. (The term “substantially” is used, because naturally some of the components, like exterior panels of aircraft, will be curved, bowed, or otherwise shaped away from a plane.) The resources involved include—among others—raw materials, machinery to process the raw material, and machinists to operate the machinery. A busy production manager may need to make numerous “business decisions” every day regarding what appears at any given moment to be the best balance of resource use given production goals and constraints.
Consider a simplified example in which a nest of metal panels is to be created for a vehicle, and the machine to cut the panels and the machinist to operate the machine are assumed to be available. The term “nest” in this context refers to an arrangement of the panels to be cut from the raw material, and the term ‘nesting’ refers to the action of preparing a nest. An example nest 1 is illustrated in FIG. 1. In some industries, the synonym “marker” is commonly used in place of “nest.”
As shown in FIG. 1, the outlines of the individual panels, such as outlines 2, are oriented on a graphical representation 3 of a sheet of material to indicate how to cut the panels to provide highly efficient use of the raw material. There are many conventional manual and software-based methods and tools used for nesting. The algorithms available for this purpose use as input the length and the width of a sheet or roll of material, additional data that indicate the sizes and shapes of the individual panels, and various rules as to what is allowed or not allowed in terms of placing the various panels on the raw material, such as panel-tilting and gap restrictions. Despite the sophistication of present-day nesting algorithms, though, less than optimal material use is still an issue. Note in FIG. 1 the large area 4 in the sheet that is not used.
The human production manager (or other person in such position) must make decisions regarding the optimization of other factors that are not included in a “nesting-only” determination. For example, if the production manager receiving the order for metal panels anticipates receiving at least three additional identical orders in the near future, he/she may decide to conserve both the human resources and the hardware and software resources for computing multiple new nests by reusing the same nest for each of the four orders as represented in FIG. 2. However, the reduced usage of the resources for designing the nests needs to be balanced against the increased usage of other resources, such as that of the raw materials. With reference again to FIG. 2, it is clear that the unused portion of raw material (areas 4) quadruples when four orders are processed instead of one, when using the same single-unit nest four times.
If instead the production manager decides to combine (“merge”) the four orders (“jobs”) of FIG. 2 into a single nest (denoted “single” despite the fact that multiple individual sheets are used), savings in raw material use would be expected. In this example, with reference to FIG. 3, a nest 5a, 5b, and 5c for the combined four orders (known also as the nest for the “merged job”) uses only three sheets of material, as opposed to four sheets, so the savings in material is clear.
Lacking an efficient method or system for weighing such a decision, it is common practice today for manufacturers to develop and store a single unit nest (or a nest for any predefined quantity) for each product or kit of parts, as in FIG. 1. Then, when the need to make this product or kit of parts arises, the nest and cutting programs are readily available, and the stored nest is retrieved and reused as many times as the product unit was ordered. Thus, in the interest of saving resources needed to redesign a nest for the exact quantity of units required, raw material is wasted by repeating the waste inherent to the single-unit nest.
There are many other considerations a production manager must make regularly when developing a production plan. For example, consider a scenario in which sheets or rolls of raw material exist in inventory, and these sheets/rolls have sizes that differ from that assumed for the predetermined nest. Such sheets or rolls could be remnants from a previous production order, and even unused sheets/rolls in an inventory can vary somewhat in dimensions. Different-sized raw materials often require different nests, because the optimal arrangement of parts may vary according to the dimensions of the raw material. Moreover, in the course of operations at a typical facility, the manufacturing processes continually consume raw material, so the stock of inventory varies by the hour, causing continual changes in the amount of “standard”-sized material and the amount and dimensions of the remnants of what was once standard-sized material pieces. It is desirable to use the material remnants when possible, as opposed to discarding (wasting) them, but then resources (human resources, time, etc.) are necessary to determine the best way to redesign the new nests for the specific dimensions of each of the remnants. Thus, in this simplified example, the final selected nest(s) is the end result of a complicated process involving two (at least) categories of variable inputs, that of the jobs and that of the available raw materials in inventory. The job data indicate the numbers and dimensions of the elements to cut, and the available raw material data indicate the quantities, sizes, and shapes of raw materials, both of the “standard” size sheets/rolls and that of the remnants of the raw materials.
Consider now two solutions to a production requirement that pairs a single job (requiring a specified number of elements of given dimensions) to two different sets of raw materials, the first set being a single unused unit (e.g., a sheet or roll) of raw material and the second set using two separate remnants (two units) of raw materials from previous jobs. The solution using the single unit is faster to cut, because the cutting machine needs to be loaded only once. Typically, though, a remnant of the sheet/roll will remain unused, and this will add to overall waste if the remnant is discarded or to costly inventory-holding expenses (so the remnant may be used for a future job). In contrast, the solution using two remnants reduces inventory-holding expenses but requires more time and human resource because two units are cut and two nests are computed.
In reality, there are far more than two production solutions to compare, and the determination of them (or any other options) is a time and resource consuming process. Therefore, in the absence of a fast automated process, production managers either limit the number of options they consider (and often do not consider more than one), and this typically causes underutilization of resources because of the lack of awareness of better undetermined options. This is the inevitable result of the lack of time, tools and resources to consider all options.
Scheduling and labor costs are also important considerations for running a manufacturing plant. For example, if human resources costs increase significantly when employees work overtime, a production manager may be motivated to avoid scheduling work at non-standard working hours. However, dividing a job over additional days may require more machine down-time because of the repeated setup periods, and that additional expense that would not exist if the job were completed in a single cutting session.
The present inventors realized that the considerations that a production manager must make are numerous and that the choices of the best trade-offs are often made based on experience and “gut instinct.” Also, many of the trade-offs are often not made by high-level production managers, but instead by low-level manufacturing personnel, because the shear number of decisions are too numerous for senior management to address personally. Thus, many decisions cannot be made with the “big picture” in mind, and the results can have very costly consequences Implementing a variation of the integrated multi-dimensional optimization described below in the present disclosure as a manual solution would have been prohibitive, due to the extensive calculations needed. Accordingly, the present inventors set out to develop a mechanism to automate and to optimize much of the decision making that previously was made in large part based on “educated guesses.” This mechanism would enable consistent and centralized decision making according to policies set by management.
Software solutions that implement certain steps, or certain facets, of the business processes described below fall under the broad categories of Business software products (for example, Enterprise Resource Planning (ERP)) or Engineering software products (for example, CAD/CAM). The lowest level entities managed by business software are typically customer orders for complete products or kits. There is marginal, if any, representation of the geometric shape of the individual pieces that comprise the product or the kit. (Such is analogous to a consumer who comes to a store to order a sofa; he does not communicate in terms of the sofa's frame, handle, or back. The atomic unit is a complete sofa, although there are many choices of complete sofas in a variety of combinations.) On the other hand, CAD/CAM software rarely deals with specific customer orders. Instead, it deals with generic products, for example, “Sofa Model 101” from a library of products offered by the business and the full details of the parts that make these products, including their geometric shape, the raw material from which they need to be cut, the characteristics of the machines on which they may be cut, and so on.
Thus, there remained an unmet need for a higher level of production resource optimization by bridging the gap between software solutions from the Business category (e.g., ERP) and software solutions from the Engineering (e.g. CAD/CAM) category and their related processes and entities.